The fusing of analytics with leading technologies can unlock significant business value and bring new transformation opportunities for enterprise companies. In order to be successful, analytics-based initiatives such as AI and the Internet of Things (IoT) need massive amounts of big data—and also
Choosing the right data management solutions as the foundation for AI is crucial. Enabling AI optimization and usability is paramount, as is easy scalability to accommodate the increasing amount of data used by AI applications. This is true no matter where you store your data: on-premises, in the
The best decisions are made by extracting value from all the disparate data across your business. Yet aggregating data across external sources, regional silos and various forms of storage is not an easy challenge to solve.
Data-powered businesses need always-on access to data to keep operations
For the past nine years, Stack Overflow, a question-and-answer website for programmers, has polled developers to understand what technologies they are using and to find out what technologies they want to work with next. This year, the nearly 90,000 survey participants revealed that, once again,
IBM continues to increase support for open source technologies. Today, we are pleased to announce that Cloud Pak for Data System now features a new capability for Postgres workloads—the IBM Performance Server for PostgreSQL.
In a previous blog, I explained how data science capabilities, massive parallel processing (MPP)
and usability improvements in data warehouse appliances can help the bottom line—and why old-fashioned architectures might not cut it. But what does that look like in practice?
Research firm Quark +
IBM’s integrated platform for Data & AI, which is 100% complimentary to Red Hat offerings. It runs on OpenShift today and has a hardware version called Cloud Pak for Data System. The beauty of Cloud Pak for Data is that it includes all of IBM’s strategic Data and AI services – including Watson
It’s no surprise: most companies working with stream data today say they are planning to make changes to drive greater value. Advancements in machine learning (ML) and very-high-speed data persistence for real-time analytics are reshaping strategies and architectures. In addition, 88 percent of
When businesses evaluate cloud infrastructure, databases or other core business systems, they nearly always consider scale as a decision factor. But scalability – the ability to grow as planning and business grows – is often overlooked for enterprise performance management.
So what do companies
While data is an enterprise’s most valuable resource when it comes to gaining competitive advantage and improving business performance, time is a critical component. Businesses run 24x7, tasking our data citizens to maximize actionable insights that will drive the actions of tomorrow.